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This paper intricately examines Vhavenda indigenous governance systems in juxtaposition with the modern administrative systems in South Africa. Through a comparative analysis using qualitative research methods and secondary data analysis, the paper reveals nuanced strengths and weaknesses in each framework, suggesting avenues for collaborative synergy and improved service provision in rural areas. Purposive and snowball sampling, along with a focus group discussion, were employed for data collection. Textbooks, academic journals, papers, and online sources were analysed. The findings not only enrich the understanding of indigenous governance but also provide actionable insights for policymakers and practitioners to enhance governance efficacy and community well-being. This paper represents a vital step towards fostering inclusive and equitable governance practices in a rapidly evolving socio-political landscape, emphasising the importance of embracing the complexities of tradition and modernity for a system that meets the diverse needs of all community members. Thus, the findings and recommendations presented in this paper are at the heart of efforts to foster sustainable development and promote social cohesion -- a foundational aspect of effective nation-building endeavours. [ABSTRACT FROM AUTHOR]

This paper provides a concise overview of Agile and DevOps methodologies in software engineering. It aims to introduce readers to the fundamental principles of Agile and DevOps, accompanied by brief descriptions and practical examples. The advantages and disadvantages of each methodology are discussed, followed by a comparative analysis highlighting key differences. Understanding these methodologies is crucial in today’s IT landscape, as they are commonly employed in various organizations, impacting project management, team collaboration, and product delivery. This paper serves as a valuable resource for individuals seeking a basic understanding of Agile and DevOps methodologies in software engineering. [ABSTRACT FROM AUTHOR]

To fill a gap in current literature, this paper analyses the impact of human factors on the operational performance of innovation hubs in the SAARC Nations and the European Union. Upon conducting an extensive examination of academic literature, four primary classifications of human factors were determined: organizational factors, individual attributes, the nature of a task and working environment. This research offers a cross-sectional analysis of these factors and their implications on innovation centres in the culturally and economically diverse domain of SAARC Nations and the European Union. The findings suggest that organizations functioning in the context of Innovation hubs in SAARC Nations, where centralized authority and value correctness is mostly emphasised on, face challenges in order to foster employee engagement and creativity. However, the innovation hubs of the European Union receive treatment from a more flexible and tolerant approach which is backed by progressive technology and is incredibly sensitive to concerns touching on ergonomics and safety of the working environment. This research highlights High performing, High committing, and High involvement management, management techniques to manage human factors to enhance operation performance. Adaptive and individual approach to the management of human variables, based on the differences in cultural and economic conditions of each region, is essential for effective development of the innovative substance and competitive advantage, the paper states. The results obtained from this study offer important guidance for the policymakers, managers and practitioners who are involved in managing and creating innovation hubs. It has provided a framework of how the organisation's operation performance may be improved through effective management of human resources. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant increase in the design of neural network models for solving math word problems (MWPs). These neural solvers have been designed with various architectures and evaluated on diverse datasets, posing challenges in fair and effective performance evaluation. This paper presents a comparative study of representative neural solvers, aiming to elucidate their technical features and performance variations in solving different types of MWPs. Firstly, an in-depth technical analysis is conducted from the initial deep neural solver DNS to the state-of-the-art GPT-4. To enhance the technical analysis, a unified framework is introduced, which comprises highly reusable modules decoupled from existing MWP solvers. Subsequently, a testbed is established to conveniently reproduce existing solvers and develop new solvers by combing these reusable modules, and finely regrouped datasets are provided to facilitate the comparative evaluation of the designed solvers. Then, comprehensive testing is conducted and detailed results for eight representative MWP solvers on five finely regrouped datasets are reported. The comparative analysis yields several key findings: (1) Pre-trained language model-based solvers demonstrate significant accuracy advantages across nearly all datasets, although they suffer from limitations in math equation calculation. (2) Models integrated with tree decoders exhibit strong performance in generating complex math equations. (3) Identifying and appropriately representing implicit knowledge hidden in problem texts is crucial for improving the accuracy of math equation generation. Finally, the paper also discusses the major technical challenges and potential research directions in this field. The insights gained from this analysis offer valuable guidance for future research, model development, and performance optimization in the field of math word problem solving. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Polonorum. Oeconomia is the property of Wydawnictwo SGGW and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The primary objective of this research paper is to conduct a comprehensive investigation into the process of developing briefs for Public–Private Partnership (PPP) projects. The study aims to outline the fundamental stages, standard processes, and critical decision points involved in this process. This is achieved through a comparative analysis of briefing frameworks used in three countries that are among the top in the PPP Market Maturity chart: The United Kingdom, Australia, and Canada. The paper discusses the stages and decision points within these countries' briefing processes, highlighting their challenges, similarities, and differences. It emphasizes the fundamental role of effective communication and coordination in PPP projects, which involve multiple stakeholders. By examining these interconnected activities and analyzing the phases, stages, and key processes constituting the briefing process, the study provides valuable insights into the PPP briefing processes in these nations. The paper concludes by proposing a conceptual process framework for brief development in PPP projects, which will be further tailored for adaptation in the PPP market in the United Arab Emirates. [ABSTRACT FROM AUTHOR]

AI chatbots have emerged as powerful tools for providing text-based solutions to a wide range of everyday challenges. Selecting the appropriate chatbot is crucial for optimising outcomes. This paper presents a comprehensive comparative analysis of five leading chatbots: ChatGPT, Bard, Llama, Ernie, and Grok. The analysis is based on a systematic review of 28 scholarly articles. The review indicates that ChatGPT, developed by OpenAI, excels in educational, medical, humanities, and writing applications but struggles with real-time data accuracy and lacks open-source flexibility. Bard, powered by Google, leverages real-time internet data for problem solving and shows potential in competitive quiz environments, albeit with performance variability and inconsistencies in responses. Llama, an open-source model from Meta, demonstrates significant promise in medical contexts, natural language processing, and personalised educational tools, yet it requires substantial computational resources. Ernie, developed by Baidu, specialises in Chinese language tasks, thus providing localised advantages that may not extend globally due to restrictive policies. Grok, developed by Xai and still in its early stages, shows promise in providing engaging, real-time interactions, humour, and mathematical reasoning capabilities, but its full potential remains to be evaluated through further development and empirical testing. The findings underscore the context-dependent utility of each model and the absence of a singularly superior chatbot. Future research should expand to include a wider range of fields, explore practical applications, and address concerns related to data privacy, ethics, security, and the responsible deployment of these technologies. [ABSTRACT FROM AUTHOR]

Objective: Parkinson's disease (PD) is one of the most prevalent neurodegenerative disorders, globally affecting approximately 120 per 100,000 people by age 70. Deep brain stimulation (DBS) is a US Federal Drug Administration (FDA)-approved and highly effective treatment for late-stage PD. However, country-specific reimbursement regulations and health policies may affect access to PD-DBS. We aimed to evaluate the uptake rate and 'treatment gap' for DBS across high-income countries. Methods: We reviewed previous literature to investigate the cost and utilisation of PD-DBS in high-income countries across Asia, Europe, Oceania, and North America (Australia, Canada, France, Germany, Hong Kong, Japan, Korea, the Netherlands, New Zealand, Norway, Spain, Switzerland, UK, and USA). Using previous estimates of DBS candidate eligibility rates, we calculated theoretical DBS uptake rates and treatment gaps nationally. Results: PD-DBS utilisation was highest in Australia and the USA and lowest in Korea and New Zealand. The total cost of PD-DBS in the first 12 months was highest in the USA and France and lowest in the UK and Germany. The utilisation rate (i.e. uptake rate) of PD-DBS (% DBS surgeries per PD case) was highest in Australia and the USA, and lowest in New Zealand and the UK, where the treatment gap reflected these trends. Conclusions: Our results highlight differences in access to DBS for PD patients among high-income countries, which we discuss in the context of health systems. Better access to effective PD treatments such as DBS is critical given the increasing prevalence of PD in an ageing world and the associated, avoidable morbidity. What is known about the topic? Deep brain stimulation (DBS) is a US Federal Drug Administration (FDA)-approved and highly effective treatment for late-stage PD; however, inequities in access to DBS for PD exist across high-income countries, likely stemming from differences in DBS cost and utilisation. What does this paper add? Our study is the first to use cost and utilisation data to calculate a PD-DBS treatment gap informing accessibility barriers. What are the implications for practitioners? The results of this study can be utilised to guide future national policy decisions and advocacy efforts by patient organisations and specialist societies. [ABSTRACT FROM AUTHOR]

In the intricate landscape of the global food system, a nuanced understanding of dynamic evolution patterns and driving mechanisms of food trade network is essential for advancing insights into the African food trade and maintaining the food security of Africa. This paper constructs a framework for analyzing the food trade network from a comparative perspective by comparing and analyzing the evolution of food trade networks in China, the United States, Russia, the European Union, and African countries. The development trend of food trade between China, Russia, the United States, the European Union, and African countries is relatively good. China, the United States, Russia, and the European Union export far more food to African countries than they import, and bilateral food trade plays an important role in alleviating food supply shortages in Africa. The food trade networks between China, the United States, Russia, the European Union, and African countries exhibit a butterfly-shaped structure centered in Africa, and the overall intensity of bilateral trade linkages is gradually increasing. France has the greatest control over the food trade network between China, the United States, Russia, the European Union, and African countries, and the influence of the United States on the food trade network between China, the United States, Russia, the European Union, and African countries is increasing. China's independence in the food trade network between China, the United States, Russia, the European Union, and African countries is enhanced, but its control ability is limited. The impact of differences in total population, differences in food production, and geographical borders on the trade network between China, the United States, the European Union, and African countries tends to decrease, while the influence of differences in the proportion of agricultural employment, differences in the arable land available for food production, and institutional distance tends to increase. [ABSTRACT FROM AUTHOR]

Multi-objective truss optimization has garnered relatively less research attention compared to single-objective scenarios. This paper presents a prescriptive and predictive analysis of nine recent multi-objective algorithms based on the Non-dominated Sorting Genetic Algorithm-2 (NSGA-2) framework. The algorithms under consideration are NSGA-2, Dynamic Neighborhood NSGA-2 (DN-NSGA-2), Decomposition-based NSGA-2 (DNSGA-2), NSGA-2 with Adaptive Real-coded Simulated Binary Crossover (NSGA-2-ARSBX), NSGA-2 with Dual Tournament Inheritance (NSGA-2-DTI), NSGA-2 with Conflict Handling (NSGA-2-conflict), Reference Point Driven NSGA-2 (RPD-NSGA-2), Grid-based NSGA-2 (g-NSGA-2) and Restricted NSGA-2 (r-NSGA-2). The study aims to evaluate the performance and effectiveness of these algorithms in terms of solution quality, convergence, coverage and diversity. Six benchmark truss optimization problems of varying complexity, ranging from 10-bar to 120-bar trusses (10-, 25-, 37-, 60-, 72- and 120-bar), are considered. The performance of the optimizers is assessed using various indicators, including Generational Distance (GD), Inverted Generational Distance (IGD), Spacing to Extend (STE) and Hypervolume (HV). The design problem targets the minimization of both structural mass and compliance while adhering to stress constraints. Experimental results reveal that NSGA-2, NSGA-2-ARSBX, r-NSGA-2 and g-NSGA-2 consistently outperform the other algorithms, providing high-quality, diverse Pareto-optimal solutions with commendable convergence properties. These algorithms also exhibit robust performance in handling truss optimization problems. [ABSTRACT FROM AUTHOR]

Optimization methods, namely, gradient optimization methods, are a key part of neural network training. In this paper, we propose a new gradient optimization method using exponential decay and the adaptive learning rate using a discrete second-order derivative of gradients. The MAMGD optimizer uses an adaptive learning step, exponential smoothing and gradient accumulation, parameter correction, and some discrete analogies from classical mechanics. The experiments included minimization of multivariate real functions, function approximation using multilayer neural networks, and training neural networks on popular classification and regression datasets. The experimental results of the new optimization technology showed a high convergence speed, stability to fluctuations, and an accumulation of gradient accumulators. The research methodology is based on the quantitative performance analysis of the algorithm by conducting computational experiments on various optimization problems and comparing it with existing methods. [ABSTRACT FROM AUTHOR]

Background: This paper investigates the impact of Ecuador's Ley Orgánica de Educación Superior (LOES), enacted in 2010, which mandated comprehensive reforms in higher education. Objective: The objective of this study is to determine whether the implementation of the LOES has led to a significant increase in academic publications in Ecuador, thereby contributing to sustainable educational practices and aligning with the Sustainable Development Goals (SDGs). In this context, sustainability refers to the ongoing capacity of higher education institutions to generate research that contributes to the long-term development of knowledge, aligns with global sustainability goals, and ensures educational practices that are responsive to societal needs. Methods: Using a synthetic control method, this study evaluates the impact of the LOES on the number of academic publications recorded in Scopus. A synthetic control consisting of data from countries with similar educational and economic profiles serves as a counterfactual to Ecuador's situation. Results: Before the LOES, the average annual number of publications was stable at 253.4 per year. Post-2010, this number surged, reaching an average of 3645.84 publications per year, representing a 358.41% increase. By 2023, the actual number of publications in Ecuador rose to approximately 6584, significantly surpassing the synthetic control estimate of 1431 publications. Conclusions: The findings confirm that the LOES has been effective in increasing research output and advancing educational sustainability in Ecuador. This analysis not only contributes to the literature on the impact of educational policies but also demonstrates the utility of synthetic control methods in assessing policy effectiveness, underscoring the potential of targeted interventions to promote academic excellence and sustainability in education. [ABSTRACT FROM AUTHOR]

This paper presents the design and analysis of PRSEUS structures with no openings, small openings, and mid-sized openings. For the typical panel structure of the small-opening PRSEUS (Pultruded Rod Stitched Efficient Unitized Structure), five reinforcement schemes are developed using different types, such as mouth frames and convex platforms. Simulation analyses of tensile and compressive load are conducted. Compared to the non-opening PRSEUS panel, the small-opening PRSEUS panel's maximum von Mises stress increases by 4.57 times under uniaxial tensile load, and the maximum von Mises stress increases by 2.55 times under uniaxial compressive load. The reinforcement efficiency of the small-opening PRSEUS panel in all five schemes exceeded 30%, Scheme E exhibits the highest load-bearing efficiency under both tensile and compressive load conditions, at 673.63 MPa/kg and 503.38 MPa/kg, respectively. For the typical PRSEUS panel structure with a mid-sized opening, three reinforcement schemes are proposed based on different methods, such as grid and cross-shaped reinforcement. These address the impact of mid-sized openings on the bearing capacity of the PRSEUS pane by analyzing the bearing efficiency of the three schemes. Compared to the non-opening PRSEUS panel, the maximum von Mises stress increases by 15.22 times under a uniaxial tensile load and by 32.45 times under a uniaxial compressive load. The reinforcement efficiency of the mid-sized-opening PRSEUS panel in these three schemes is greater than 50%, with Scheme III providing the highest bearing efficiency under a tensile load at 20.74 MPa/kg and 50.66 MPa/kg under a compressive load. [ABSTRACT FROM AUTHOR]

Copyright of Multi-Knowledge Electronic Comprehensive Journal For Education & Science Publications (MECSJ) is the property of Multi-Knowledge Electronic Comprehensive Journal For Education & Science Publications (MECSJ) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study comprehensively compares and analyzes eight representative global frameworks for teacher Information and Communication Technology (ICT) competencies, each reflecting regional educational priorities and philosophies. The research aims to transcend geographical boundaries by identifying consensus on key areas of teacher ICT competencies and exploring unique characteristics of each framework within specific educational contexts and challenges. The findings indicate that despite diversity, global teacher ICT competencies represent an integration of knowledge, skills, and values, particularly in digital society building, digital career development, digital communication and collaboration, digital assessment, digital teaching and learning, and development of students' digital competencies. The study further highlights varying emphasizes among frameworks in core areas and competencies, accompanied by varying levels of implementation support. Ultimately, the paper provides recommendations to assist educators, policymakers, and digital leaders in understanding global standards for teacher ICT competencies, developing effective and inclusive frameworks, and exploring best practices for advancing teacher ICT competencies. [ABSTRACT FROM AUTHOR]

Copyright of China Fiber Inspection is the property of China Fiber Inspection and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Multi-modal fusion technology gradually become a fundamental task in many fields, such as autonomous driving, smart healthcare, sentiment analysis, and human-computer interaction. It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities. Under complex scenes, multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions. However, achieving outstanding performance is challenging because of equipment performance limitations, missing information, and data noise. This paper comprehensively reviews existing methods based on multi-modal fusion techniques and completes a detailed and in-depth analysis. According to the data fusion stage, multi-modal fusion has four primary methods: early fusion, deep fusion, late fusion, and hybrid fusion. The paper surveys the three major multi-modal fusion technologies that can significantly enhance the effect of data fusion and further explore the applications of multi-modal fusion technology in various fields. Finally, it discusses the challenges and explores potential research opportunities. Multi-modal tasks still need intensive study because of data heterogeneity and quality. Preserving complementary information and eliminating redundant information between modalities is critical in multi-modal technology. Invalid data fusion methods may introduce extra noise and lead to worse results. This paper provides a comprehensive and detailed summary in response to these challenges. [ABSTRACT FROM AUTHOR]

Energy storage technology is an essential part of the efficient energy system. Compressed air energy storage (CAES) is considered to be one of the most promising large-scale physical energy storage technologies. It is favored because of its low-cost, long-life, environmentally friendly and low-carbon characteristics. The compressor is the core component of CAES, and the performance is critical to the overall system efficiency. That importance is not only reflected in the design point, but also in the continuous efficient operation under variable working conditions. The diagonal compressor is currently the focus of the developing large-scale CAES because of its stronger flow capacity compared with traditional centrifugal compressors. And the diagonal compressor has the higher single stage pressure ratio compared with axial compressors. In this paper, the full three dimensional numerical simulation technologies with synergy theory are used to compare and analyze the internal flow characteristics. The performance of the centrifugal and diagonal impellers that are optimized under the same requirements for large-scale CAES has been analyzed. The relationship between the internal flow characteristics and performance of the centrifugal and diagonal impellers with the change of mass flow rates and total inlet temperature is given qualitatively and quantitatively. Where the cosine value of the synergy angle is high, the local flow loss is large. The smaller proportion of the positive area is the pursuit of design. Through comparative analysis, it is concluded that the internal flow and performance changes of centrifugal and diagonal impellers are different. The results confirm the superiority and feasibility of the off-design performance of the diagonal compressor applied to the developing large-scale CAES. [ABSTRACT FROM AUTHOR]

This paper presents an experimental comparison of two types of Li-ion battery stacks for low-voltage energy storage in small urban Electric or Hybrid Electric Vehicles (EVs/HEVs). These systems are a combination of lithium battery cells, a battery management system (BMS), and a central control circuit—a lithium energy storage and management system (LESMS). Li-Ion cells are assembled with two different active cathode materials, nickel–cobalt–aluminum (NCA) and lithium iron phosphate (LFP), both with an integrated decentralized BMS. Based on experiments conducted on the two assembled LESMSs, this paper suggests that although LFP batteries have inferior characteristics in terms of energy and power density, they have great capacity for improvement. [ABSTRACT FROM AUTHOR]

The paper deals with a new method of innovative assessment of the supported effects and ecosystem services of forests using the actual amount of their increased costs. Among the most important research findings and signifi- cance of the new method is that it contributes to the body of knowledge on valuation and payment for ecosystem services. The focus of the research task is to help address the current difficult economic situation of forest owners resulting from the impacts of climate change. The study aims to determine what work quantifies the amount of compensation for the provision of supported ecosystem services that is sufficient for owners by using hypothesis testing. The evaluation of the supported effects was carried out in a case study in the area of the Chrudim-Podhůra Recreational Forests in the Czech Republic. The results of the evaluation were quantified in two experimental spreadsheets of the results, a comparative analysis of the evaluation results was performed, and hypothesis testing was conducted. The innovative methodological approach to the assessment of supported effects can be easily modified and used to assess the actual amount of increased costs of other ecosystem services of the forest. [ABSTRACT FROM AUTHOR]

Accurately estimating Battery State of Charge (SOC) is essential for safe and optimal electric vehicle operation. This paper presents a comparative assessment of multiple machine learning regression algorithms including Support Vector Machine, Neural Network, Ensemble Method, and Gaussian Process Regression for modelling the complex relationship between real-time driving data and battery SOC. The models are trained and tested on extensive field data collected from diverse drivers across varying conditions. Statistical performance metrics evaluate the SOC prediction accuracy on the test set. Gaussian process regression demonstrates superior precision surpassing the other techniques with the lowest errors. Case studies analyse model competence in mimicking actual battery charge/discharge characteristics responding to changing drivers, temperatures, and drive cycles. The research provides a reliable data-driven framework leveraging advanced analytics for precise real-time SOC monitoring to enhance battery management. [ABSTRACT FROM AUTHOR]

This research paper investigates the efficacy of various machine learning algorithms in predicting stress levels. By employing a diverse set of algorithms, including [List of Algorithms], we aim to identify the most accurate and reliable model for stress prediction. The study utilizes [Dataset Information] to train and test the algorithms, evaluating their performance based on metrics such as accuracy, precision, recall, and F1 score. The findings will contribute to the development of more effective stress prediction models, with potential applications in healthcare, workplace wellness, and personal well-being. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of Ablai Khan KazUIRandWL: Series 'International Relations & Regional Studies' is the property of Kazakh Ablai Khan University of International Relations & World Languages and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of the paper is to study foreign experience in regulating the mediation procedure. Notable among the methods employed are logical analysis, dogmatic, formal legal, legal hermeneutics, deduction, synthesis, and other methods. In the course of the research, the institute of mediation was considered: the concept was studied, the role in the modern world was highlighted, its inherent features and principles of implementation were identified. The legislative base of the Republic of Kazakhstan and a number of foreign states was studied, which made it possible to highlight certain features. A comparative legal analysis of the foreign experience of the mediation procedure was carried out, in particular, the experience of the USA, Great Britain, Germany and France. The findings offer solutions to issues that will improve Kazakhstan's mediation procedure law enforcement. [ABSTRACT FROM AUTHOR]

This paper offers a comparative analysis of internationalization policy between two distinct nations entrenched in unique sociopolitical and economic cultures, namely Japan and the United States of America (U.S.A.). How do different policymaking processes impact internationalization policy in practice? While Japan's internationalization policy is clearly articulated at the national level, the U.S. does not have a national higher education internationalization policy that emanates from the federal government. Therefore, in this study we analyzed macro-level data from three distinct policymaking sectors to identify U.S. national policy. Our analysis identifies the policy-making process in each nation and elucidates how internationalization policy unfolded in both cases. Second, we compare the development of higher education internationalization policy efforts in the two countries, sequencing events, factors, and rationales that impacted national policy. This approach allowed us to compare the implications of having a centralized versus a pluralistic internationalization policy-making process in the 2000s. Our research shows that, in practical terms, there is more variation in higher education internationalization policy in the U.S. than in Japan. In both countries, policy dynamics were influenced by social and economic factors, and political factors influenced policy in the U.S. An academic and humanitarian rationale for internationalization policy was not central to the essence of the policy in either country. [ABSTRACT FROM AUTHOR]

Relevance. Enhancing the development of the machinery manufacturing sector significantly contributes to realizing sustainable economic development goals, thereby fostering sustainable growth opportunities across various scales, ranging from local to global. The active advancement of the machine-building sector, which serves as the foundation for sustainable societal progress, demands careful consideration of key factors for the effective operation of machinery manufacturing enterprises with investments being one of the foremost. This highlights the imperative for comprehensive research into the tangible impact of investments in securing the sustainable growth of machine-building businesses. Objective. The paper targets the conduct of analytical research on investment practices and approaches adopted by machine-building enterprises in European Union countries to specify the key investment factors for their sustainable development. Methods. The research is based on both general scientific and specialized methods of economic theory, including methods of theoretical synthesis and comparative analysis. Throughout the research, statistical data from the European Union regarding the operation and performance of machinery manufacturing enterprises were utilized and processed using analysis methods, including comparison, grouping, calculation of averages, and absolute growth. Furthermore, a rating methodology was implemented to identify European Union member states exhibiting the most favorable indicators about the status and dynamics of the machine-building industry. Results. A comprehensive analysis of contemporary scholarly advancements regarding the examination of the role of investments and effective methodologies for their implementation within the machine manufacturing industry was conducted. A grouping of 22 European Union member states was undertaken based on the criteria of the number of machine-building enterprises and indicators of its absolute growth over a ten-year temporal span. The 22 EU member states are grouped by the parameters of the number of machine-building enterprises and their absolute growth over a tenyear period. The average revenue and gross income per enterprise in the selected countries of the European Union’s machinery sector were studied, and based on the results, a ranking was conducted. Utilizing the established ranking of the top selected countries, a comprehensive analysis of key investment indicators was conducted, focusing on parameters that include investments in tangible assets, machinery and equipment, as well as human resources. An overview of investment practices by machinery manufacturing enterprises was undertaken, resulting in the identification of their respective strengths and weaknesses. [ABSTRACT FROM AUTHOR]

This paper introduces a rigorous and comprehensive approach to the assessment of marine shafting systems through the utilization of an advanced π-Theorem-based scaling methodology. Integrating journal-bearing similarity assessment and shaft-line scaling methodology with advanced dimensional analysis, the study aims to provide a methodology foundation for systematic replication and analysis of marine shafting systems through scaled models. The proposed scaling methodology ensures geometric and mechanical similarity in terms of shaft-line deflection, considering key scaling parameters such as shaft length, diameter, weight, loads, rotational speed, material properties, bearing locations, and offsets. The advanced dimensional analysis computes specific non-dimensional ratios to guarantee a close resemblance between a real-size system and a scaled lab model. The methodology is analytically derived and validated with numerical simulations for a case study, conducting comparative analysis, evaluating discrepancies, and utilizing the integrated framework for experimentation. [ABSTRACT FROM AUTHOR]

This paper presents the results of a comparative analysis of approaches for practical modelling of educational ecosystems, understood as integrating autonomous systems and actors in the field of education into unified functional networks. The methodology of the mixed-methods study combines conceptual content analysis of a selected sample of 121 thematically related publications indexed in global databases in the period 2005 – 2024 with case study analysis covering 51 educational practices in the Bulgarian and international context. The implemented comparative analysis allowed to identify the main conditions and factors facilitating the transition from systemic to ecosystemic modelling and functioning in the educational sphere. The results of the content analysis of foreign models and practices allowed to formulate identified potential opportunities for the adaptation of global practical models of educational ecosystems in the conditions of Bulgarian education. [ABSTRACT FROM AUTHOR]

Purpose: The main purpose of the article is to highlight the importance of CSR and USR, evaluate CSR practices in Polish public universities of economics, and provide actionable recommendations for improving CSR practices at universities. Design/methodology/approach: A comparative analysis of the 5 main economic universities in Poland was carried out on the basis of publicly available online sources. Findings: Overall, the findings indicate that Polish public economic universities are actively engaged in implementing CSR strategies. Their activities are diverse and tailored to their specific contexts, evidencing a strong commitment to promoting sustainable development, ethical conduct, and societal well-being. The research highlights successful strategies and provides recommendations that can serve as a valuable resource for enhancing CSR practices in higher education. Research limitations/implications: While this research provides a comprehensive overview of CSR practices at major public economic universities in Poland, future studies should address these limitations and expand the scope of analysis to include diverse perspectives, rigorous quantitative measures, and broader institutional contexts. Practical implications: The research provides valuable insights and practical recommendations that can significantly enhance the implementation of CSR practices in higher education institutions. By adopting these recommendations, universities can improve their societal and environmental impacts, enhance stakeholder engagement, foster innovation, and achieve a competitive edge in the education sector. The commercial and economic implications highlight substantial benefits not only for the universities but also for the broader communities they serve. Social implications: The research has significant social implications that extend beyond the academic community. It can influence public attitudes towards CSR, drive corporate and environmental responsibility, inform public and industry policies, and enhance the quality of life. By showcasing the positive impact of CSR initiatives in universities, the research can inspire wider adoption of ethical and sustainable practices across various sectors, contributing to a more equitable and sustainable society. Originality/value: The paper makes significant contributions by offering a detailed comparative analysis of CSR practices in Polish economic universities, integrating CSR and USR concepts, providing actionable recommendations, and addressing a broad audience. Its novel insights and practical guidance have the potential to influence the development and implementation of CSR strategies, fostering a culture of sustainability and social responsibility in the higher education sector. [ABSTRACT FROM AUTHOR]

Facial emotion recognition (FER) is the technology or process of identifying and interpreting human emotions based on the analysis of facial expressions. It involves using computer algorithms and machine learning techniques to detect and classify emotional states from images or videos of human faces. Further, FER plays a vital role in recognizing and understanding human emotions to better interpret someone's feelings, intentions, and attitudes. In the present time, it is widely used in various fields such as healthcare, human–computer interaction, law enforcement, security, and beyond. FER has a wide range of practical applications across various industries including Emotion Monitoring, Adaptive Learning, and Virtual Assistants. This paper presents a comparative analysis of FER algorithms, focusing on deep learning approaches. The performance of different datasets, including FER2013, JAFFE, AffectNet, and Cohn–Kanade, is evaluated using convolutional neural networks (CNNs), deep face, attentional convolutional networks (ACNs), and deep belief networks (DBNs). Among the tested algorithms, DBNs outperformed other algorithms, reaching the highest accuracy of 98.82%. These results emphasize the effectiveness of deep learning techniques, particularly DBNs, in FER. Additionally, outlining the advantages and disadvantages of current research on facial emotion identification might direct future research efforts in the direction of the most profitable directions. [ABSTRACT FROM AUTHOR]

This paper presents the results of a comparative analysis of approaches for practical modelling of educational ecosystems, understood as integrating autonomous systems and actors in the field of education into unified functional networks. The methodology of the mixed-methods study combines conceptual content analysis of a selected sample of 121 thematically related publications indexed in global databases in the period 2005 – 2024 with case study analysis covering 51 educational practices in the Bulgarian and international context. The implemented comparative analysis allowed to identify the main conditions and factors facilitating the transition from systemic to ecosystemic modelling and functioning in the educational sphere. The results of the content analysis of foreign models and practices allowed to formulate identified potential opportunities for the adaptation of global practical models of educational ecosystems in the conditions of Bulgarian education. [ABSTRACT FROM AUTHOR]

In this paper, an economical unconditionally stable method of variable directions with extrapolation of numerical solutions of problems for parabolic equations containing mixed derivatives is proposed and justified by approximation and stability, which, in comparative analysis with other numerical methods, showed the highest accuracy and a unique margin of stability when changing grid characteristics. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Sciences Institute is the property of Lublin University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fingerprint patterns are unique and reliable for identification. This research paper focuses on a comparative analysis to determine the inheritance of fingerprint patterns within Indian families. The sample collection process for this comparative analysis involved working with 10 families. The study aims to gain insights into the hereditary aspects of fingerprint characteristics among the Indian population. The research methodology involves the collection of fingerprints and the analysis of patterns using microscopes, magnifying lenses, and software. The results reveal both class and individual characteristics within fingerprints, contributing to our understanding of dermatoglyphics. The average class characteristics percentage totals around 71.5%, with an average individual characteristic percentage of approximately 13.6%. The research has implications for forensic investigations, genetics, and personal identification systems. Further studies with larger sample sizes and genetic analysis integration are recommended for future research. [ABSTRACT FROM AUTHOR]

This paper explores the origins, pedagogical aims and framework of the Hungarian University Film Award (HUFA) incorporating the personal experience of its author who participated in the coordination of various stages of the initiative. It claims that the initiative created a unique learning environment—an educational corpus comprising of six films from 2019 competing for the awards—and describes the methods and conceptual angles used in class discussions. The first part of the article outlines the interpretive framework offered for students to better grasp the general aesthetic and generic patterns at work in the corpus, including the emergence of a medium concept film in Hungarian film culture. The second part introduces another framework that helped students to contextualize the corpus by organizing films into two groups based on festival appearances and international visibility. The final part of the paper focuses on interpretations proposed by students, the ways they used the analytical methods of integration and differentiation while addressing the HUFA-corpus. This includes reconstructing key arguments as to how in-class debates mapped up, compared, and criticised the manifold strategies films employ to raise awareness towards traumatic experience. The pedagogical benefits of the initiative were most apparent in this stage, where students were expected to consider both individual films and an overarching trauma-discourse. [ABSTRACT FROM AUTHOR]

While the link between the urban network and institutional context has been well established, there has been less work on the effect of shifting political economy on the mechanism of its intercity flows. In this paper, the investment dataset of Chinese publicly listed firms is used to construct corporate‐based urban networks with different ownership structures. Two straightforward but effective comparative analyses are conducted. The first distinguishes between networks formed by state‐controlled and nonstate‐controlled firms, and the second distinguishes between subnetworks formed by central‐ and local‐state power. By surveying the distinctions from the perspectives of state–market relations and central‐local government relations, we argue that the urban network in China is shaped by the varied forms in which the central government, local governments, and the private sector interact. To gain a more proper knowledge of the geographical patterns, this research recommends further field research into enterprise‐based linkages of multiple ownership. [ABSTRACT FROM AUTHOR]

Given the significance of economic development, this paper undertakes a comparative assessment and analysis of the level of economic development among South American countries. Initially, a modified ITARA method was applied to determine criteria weights through the examination of real data. Subsequently, a modified version of AROMAN was introduced and utilized in conjunction with the RAM method to prioritize the nine countries based on eight economic development indicators. The findings from the modified AROMAN method indicate that Brazil ranks first among the nine studied countries in South America in terms of economic development indicators, while Argentina occupies the last position (ninth). The results obtained from the RAM method for assessing the economic development level of the 9 South American countries based on the eight examined indicators exactly align with the findings calculated from the modified AROMAN method. The RIV method has been used to validate and confirm the findings obtained from the modified AROMAN and RAM methods. The results obtained from the RIV method are consistent with those of the modified AROMAN and RAM methods. Therefore, the findings exhibit a high level of validity and reliability. The research results indicate that economic development among South American countries is not uniform. [ABSTRACT FROM AUTHOR]

Although Business Intelligence (BI) and Business Analytics (BA) have been widely adopted in the tourism sector, comparative research using BI and BA remains scarce. To fill this gap in the literature, the present study explores how BI and BA contribute to strategic innovation, address operational challenges, and enhance customer engagement. To this end, using a dual-method approach that incorporates both quantitative and qualitative methodologies, we first conduct a bibliometric analysis using SciMAT. This sets the stage for the subsequent application of the Gioia methodology. Specifically, we perform an in-depth qualitative examination of a total of 12 scholarly articles on the tourism sector, evenly split between BI and BA. Upon synthesizing the findings on the roles of BI and BA, we outline distinct pathways through which they influence tourism sector management solutions. Based on the obtained evidence, we argue that, while BI focuses on technological advancement and operational integration, BA is more aligned with predictive analytics and data-driven customer engagement. These insights provide managers with a better understanding of the roles of BI and BA, serving as a guide for their strategic applications, from improving service quality to innovating in customer engagement. The novelty of this approach lies in its use of the Gioia methodology, in a comparative analysis to evaluate the separate yet complementarily roles of BI and BA, and in enhancing tourism industry practices. [ABSTRACT FROM AUTHOR]

In recent years, China has launched a number of Gaofen (GF) series earth observation satellites. It is crucial to understand the relationship between the data of the GF series of satellite sensors for the selection of sensor images for scientific research. Taking the same-day transit image pairs of three regions as the study data, this paper compares the consistency of the Top of Atmosphere (TOA) reflectance of GF-1 WFV4 and GF-6 WFV sensors by using the TOA mean comparison method, and discusses the differences in water body and vegetation extraction. The results indicate that the satellite signal intensity in different land cover types and areas differs significantly. In the bare soil-dominated region, GF-1 WFV4 has a larger signal strength than GF-6 WFV, while in the vegetation-dominated region, it turns out to be just the opposite. The difference between the two sensors is mainly related to the difference in the spectral response function and the radiometric resolution of the two satellites. In addition, the determination coefficient (R2) of the corresponding bands of the two sensors is all greater than 0.90, indicating that the two sensors have strong linear correlation and good complementarity. [ABSTRACT FROM AUTHOR]

The efficiency of poultry production plays a crucial role in ensuring food security and maintaining human health sustainability. Although extensive research has been done on the largest poultry-producing countries, the European Union's contribution has not been thoroughly investigated, especially in Central and Eastern Europe. This study aims to fill this gap by analysing the technical efficiency of poultry farms in Hungary and Poland. We use the stochastic metafrontier approach to Farm Accountancy Data Network (FADN) data from 2010 to 2015. The results suggest that both countries have technical inefficiencies. The meta technical efficiency (MTE) was higher in Poland than in Hungary, driven by both a higher technology gap ratio (TGR) and higher (country-specific) technical efficiency (TE) in Poland. In both countries, returns to scale were increasing, which suggests that policies that increase scale of operation could increase efficiency. Furthermore, the study highlights the importance of technological gaps for several farms both in Poland and Hungary; therefore, policies should also focus on supporting investments in technology adoption and innovation. This could involve providing subsidies or grants for the adoption of advanced farming technologies, such as automated feeding systems or data analytics for optimizing production processes. [ABSTRACT FROM AUTHOR]

Cities located in the Arctic often have extreme geographic and environmental contexts and unique sociopolitical and economic trajectories that, when combined with amplified effects of climate change in the region, impact future sustainable development. Well-recognized and standardized sustainable development indicator (SDI) frameworks such as ISO 37120 or UN-Habitat City Prosperity Index are often used to compare data across cities globally using comprehensive sets of indicators. While such indexes help characterize progress toward development and guide short- and long-term decision-making, they often lack relevance to specific contexts or characterize future visions of urban growth. To evaluate the extent of these deficiencies and to provide a comparative analysis of approaches to sustainable urban growth in the Arctic, this paper analyzes city planning documents for five northern cities - Anchorage (USA), Utqiagvik (USA), Reyjavik (ISL), Iqaluit, (CAN), Whitehorse, (CAN) - for goals, targets, and indicators and compare these to thematic areas and indicators defined by ISO 37120:2018 Sustainable Cities and Communities. The results confirm that although international SDI frameworks may be useful for comparative analysis of cities across diverse regions, they exclude important local factors that influence goal-oriented urban sustainability planning strategies employed in the Arctic region. [ABSTRACT FROM AUTHOR]

The paper aims to empirically investigate the role of price-related marketing stimuli and the visual appeal of the user interface (UI) on online impulse buying. The mediating effects of cognitive and affective components, which are influenced by price-related and visual-appeal UI, on online impulse buying are checked. A survey-based research design was employed by floating the structured questionnaire among 370 respondents in both online and offline modes. These responses were further analyzed using covariance-based structural equation modeling (SEM) and AMOS software. The result of the study indicated that affective shopping behavior, visual appeal of the website, and cognitive shopping behavior significantly influence online impulsive buying compared to price-related stimuli. Though the direct effect of price-related stimuli on online shopping is insignificant, its indirect effect via affective shopping behavior is highly significant. Meanwhile, the website's visual appeal, directly and indirectly, affects online shopping behavior. It was also found that affective shopping behavior fully mediates between price-related marketing stimuli and online impulsive buying. In contrast, cognitive shopping behavior is partially mediated by the visual appeal of UI and online impulsive buying. The research results direct that people may engage in online impulsive buying mainly due to affective shopping behavior and the visual appeal of the UI, but at the same time, they are equally price conscious. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Silk is the property of Zhejiang Sci-Tech University Magazines and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One of the dominant global development agendas for rural Africa in the past two decades has cast large-scale agro-industrial investments as a solution to achieve more efficient land use, higher crop yields, enhanced food security, and poverty reduction, among others. However, mounting evidence shows that this agenda has not fulfilled its promises: most land deals for agricultural production have not materialised as planned and their socio-economic development objectives often remain unreached. Despite the often severe impacts of non-operational projects, knowledge about why they fail to take place and operate remains fragmentary. Based on an extensive literature review of contemporary land deals in seven sub-Saharan countries, this paper sheds light on two 'productive gaps'. First, the article delves into the 'productive gap' of land deals themselves, identifying key drivers of non-operational land deals. The reviewed literature points to local opposition and financial difficulties as significant factors impacting agricultural operations. Local opposition, in turn, stems largely from flawed land acquisition processes and unfulfilled investors' promises. Second, this article offers a critical appraisal of the biases and oversights in the knowledge the land grab scholarship has 'produced'. [ABSTRACT FROM AUTHOR]

Around 50 million individuals worldwide suffer from epilepsy, a chronic, non-communicable brain disorder. Several screening methods, including electroencephalography, have been proposed to identify epileptic episodes. EEG data, which are frequently utilised to enhance epilepsy analysis, offer essential information on the electrical processes of the brain. Prior to the emergence of deep learning (DL), feature extraction was accomplished by standard machine learning techniques. As a result, they were only as good as the people who made the features by hand. But with DL, both feature extraction and classification are fully automated. These methods have significantly advanced several fields of medicine, including the diagnosis of epilepsy. In this paper, the works focused on automated epileptic seizure detection using ML and DL techniques are presented as well as their comparative analysis is done. The UCI-Epileptic Seizure Recognition dataset is used for training and validation. Some of the conventional ML and DL algorithms are used with a proposed model which uses long short-term memory (LSTM) to find the best approach. Post that comparative analysis is performed on these algorithms to find the best approach for epileptic seizure detection. As a result, the proposed model LSTM gives a validation accuracy of 97% giving the most appropriate and precise result as compared to other mentioned algorithms used in this study. [ABSTRACT FROM AUTHOR]

PURPOSE: This study aims to identify the differences and similarities in the innovation systems of developing vs. developed countries that influence SMEs' adoption of Fourth Industrial Revolution (4IR) technologies. There is a notable absence of comparative research between National Innovation Systems (NIS) of developing and developed countries. Additionally, the current scholarly conversation lacks a holistic view of NIS. Our study aims to fill these gaps by employing Lundvall's framework to explore both developed and developing countries' systems comprehensively. METHODOLOGY: The data was collected through a Systematic Literature Review, identifying a total of 695 publications from SCOPUS, Web of Science (WoS), and ProQuest. The PRISMA process was adhered to, resulting in 32 papers undergoing quality evaluation using Gough's 'weight of evidence' guidelines. Twenty-nine primary papers were selected, comprising twelve from developed countries, another twelve from developing countries, and the remainder from both categories. Using Qualitative Meta-synthesis (QMS) with ATLAS.ti, a systematic alignment of codes with research inquiries pertaining to NIS ensued, revealing a multifaceted spectrum of findings across these scholarly investigations. FINDINGS: We found that there are similarities and differences between the innovation systems of developed and developing nations. The similarities include the intra-firm interactions taking place between managers and workers, inter-firm relations between the SMEs and Academia and other SMEs, as well as the role of the government in providing funding and regulation (albeit at significantly varying degrees). The most significant differences observed were in the funding mechanisms, the role of the government, and the R&D systems. It was found that governments in developed countries provided SMEs with substantial incentives, tax credits, and subsidies to adopt 4IR technologies, which appears to positively impact the adoption rate. We conclude by developing a conceptual framework for the NIS necessary for the adoption of SMEs' 4IR technologies in developing countries. IMPLICATIONS: This study contributes to the literature on innovation systems by examining the NIS of both developed and developing countries. This analysis allows us to gain deeper insights into how specific aspects of each country (developed or developing) affect (positively or negatively) SMEs' adoption of 4IR technologies. Practically, it informs governments in developing countries on which aspects to focus on in their NIS to increase the rate of the adoption of 4IR technologies by SMEs. ORIGINALITY AND VALUE: A distinctive aspect of this study lies in the creation of a comprehensive conceptual model delineating the essential components of the innovation system pivotal for the successful integration of 4IR technologies within SMEs. This model is designed to serve as a practical tool for governments in developing countries, providing a structured framework to facilitate and enhance the strategic development of their innovation landscapes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Sciences Institute is the property of Lublin University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper represents a comparative study that explores the governmental vaccine advertising campaigns that were authorised by two English-speaking and two German-speaking countries – namely Australia, Britain, Austria and Germany – within the context of the global SARS-CoV-2 pandemic. The data set in question comprises 40 vaccination posters issued by each country's respective government between January 2021 and July 2022, all of which were displayed in public spaces. The study aims to explore how national governments use their ideological foothold to persuade their respective populations to take action against the virus by getting vaccinated, thus demonstrating how ideology and persuasion are interrelated in governmental vaccine campaigns across countries. In terms of methodology, this comparative study employs primarily methods of Multimodal Critical Discourse Analysis (MCDA). The strategies identified in the four countries under investigation concentrate largely on two key strategies: (1) providing a sense of community and solidarity; (2) issuing warnings and eliciting a sense of fear. The discourses of the German-speaking countries gravitate towards the discursive strategy of community, with Austria constituting a notable exception. In contrast, the Anglophone discourse in Britain and Australia employs strategies involving fear and warning, although their campaigns differ in terms of the intensity of the discourse they employ. [ABSTRACT FROM AUTHOR]

Background: Non-invasive prenatal testing (NIPT), which can screen for aneuploidies such as trisomy 21, is being implemented in several public healthcare systems across Europe. Comprehensive communication and information have been highlighted in the literature as important elements in supporting women's reproductive decision-making and addressing relevant ethical concerns such as routinisation. Countries such as England and France are adopting broadly similar implementation models, offering NIPT for pregnancies with high aneuploidy probability. However, we do not have a deeper understanding of how professionals' counselling values and practices may differ between these contexts. Methods: In this paper, we explore how professionals in England and France support patient decision-making in the provision of NIPT and critically compare professional practices and values. We draw on data from semi-structured interviews with healthcare professionals. Results: Both English and French professionals emphasised values relating to patient choice and consent. However, understandings and application of these values into the practice of NIPT provision differed. English interviewees placed a stronger emphasis on interpreting and describing the process of counselling patients and clinical care through a "principle" lens. Their focus was on non-directiveness, standardisation, and the healthcare professional as "decision-facilitator" for patients. French interviewees described their approach through a "procedural" lens. Their focus was on formal consent, information, and the healthcare professional as "information-giver". Both English and French professionals indicated that insufficient resources were a key barrier in effectively translating their values into practice. Conclusion: Our findings illustrate that supporting patient choice in the provision of NIPT may be held as an important value in common on a surface level, but can be understood and translated into practice in different ways. Our findings can guide further research and beneficially inform practice and policy around NIPT provision. [ABSTRACT FROM AUTHOR]